fix: embedders imports (#153)

Author: andhreljaKern

src/embedders/__init__.py

@@ -3,7 +3,7 @@
 from spacy.tokens.doc import Doc
 from sklearn.decomposition import PCA
 from tqdm import tqdm
-from embedders import util
+from src.embedders import util
 from joblib import dump, load
 
 
@@ -112,7 +112,7 @@ def __init__(
         embedder: Embedder,
         n_components: int = 8,
         autocorrect_n_components: bool = True,
-        **kwargs
+        **kwargs,
     ):
         super().__init__()
         self.embedder = embedder
@@ -126,15 +126,15 @@ def store_pca_weights(self, file_name: str):
         Args:
             file_name (str): Path to the file without any file endings.
         """
-        dump(self.reducer, f'{file_name}.joblib') 
+        dump(self.reducer, f"{file_name}.joblib")
 
     def load_pca_weights(self, file_name: str):
         """Loads the PCA weights from a file.
 
         Args:
             file_name (str): Path to the file without any file endings.
         """
-        self.reducer = load(f'{file_name}.joblib')
+        self.reducer = load(f"{file_name}.joblib")
 
     @abstractmethod
     def _reduce(

src/embedders/classification/__init__.py

@@ -1,4 +1,4 @@
-from embedders import Embedder
+from src.embedders import Embedder
 
 
 class SentenceEmbedder(Embedder):

src/embedders/classification/contextual.py

@@ -1,7 +1,7 @@
 from typing import List, Optional, Union, Generator
 from sentence_transformers import SentenceTransformer
-from embedders import util
-from embedders.classification import SentenceEmbedder
+from src.embedders import util
+from src.embedders.classification import SentenceEmbedder
 from spacy.tokens.doc import Doc
 import torch
 import openai

src/embedders/classification/count_based.py

@@ -1,8 +1,8 @@
 from typing import List, Union, Generator
 from sklearn.feature_extraction.text import CountVectorizer
 from sklearn.feature_extraction.text import TfidfVectorizer
-from embedders.classification import SentenceEmbedder
-from embedders import util
+from src.embedders.classification import SentenceEmbedder
+from src.embedders import util
 
 
 class CountSentenceEmbedder(SentenceEmbedder):

src/embedders/classification/reduce.py

@@ -1,7 +1,7 @@
 from spacy.tokens.doc import Doc
 from typing import Union, List, Generator
 import numpy as np
-from embedders import PCAReducer, util
+from src.embedders import PCAReducer, util
 
 
 class PCASentenceReducer(PCAReducer):

src/embedders/extraction/__init__.py

@@ -1,5 +1,5 @@
 import spacy
-from embedders import Embedder
+from src.embedders import Embedder
 from spacy.tokens.doc import Doc
 from typing import Union
 

src/embedders/extraction/contextual.py

@@ -5,12 +5,12 @@
 import re
 from transformers import AutoTokenizer, AutoModel
 from collections import defaultdict
-from embedders import util
+from src.embedders import util
 from spacy.tokens.doc import Doc
 
 
-from embedders.enums import WarningType
-from embedders.extraction import TokenEmbedder
+from src.embedders.enums import WarningType
+from src.embedders.extraction import TokenEmbedder
 
 
 class TransformerTokenEmbedder(TokenEmbedder):

src/embedders/extraction/count_based.py

@@ -1,9 +1,9 @@
 from typing import List, Generator, Union
 from sklearn.feature_extraction.text import CountVectorizer
-from embedders import util
+from src.embedders import util
 from spacy.tokens.doc import Doc
 
-from embedders.extraction import TokenEmbedder
+from src.embedders.extraction import TokenEmbedder
 
 
 class BagOfCharsTokenEmbedder(TokenEmbedder):

src/embedders/extraction/reduce.py

@@ -1,6 +1,6 @@
 from typing import List, Generator, Union
 import numpy as np
-from embedders import PCAReducer, util
+from src.embedders import PCAReducer, util
 
 
 class PCATokenReducer(PCAReducer):